High-level background noise in a wired or wireless telecommunications channel degrades in-band signaling and lowers the perceived voice quality of speech signals. To ensure quality of service in voice-band transmission, noise suppressors, or noise reducers, are used to reduce the degradation caused by the background noise and to improve the signal-to-noise ratio (SNR) of noisy signals.
Many popular noise reduction/suppression algorithms use the principles of spectral weighting. Spectral weighting means that different spectral regions of the mixed signal of speech and noise are attenuated or modified with different gain factors. The goal is to obtain a speech signal that contains less noise than the original speech signal. At the same time, the speech quality must remain substantially intact with a minimal distortion of the original speech.
Spectral weighting is typically performed in the frequency domain using the well-known Fourier transform. Voice activity detectors are used to determine whether current signal samples represent predominantly voice or noise. Energy estimators and signal-to-noise ratio estimators are used to calculate a factor that is then used to modify the level of a frequency-domain signal. The signal to noise ratio is a measure of signal strength (e.g., voice strength) relative to background noise. The frequency-domain signal as modified is then converted back to the time-domain.
One problem with noise suppressors is that the level of suppression can be too high or too low under various different conditions. Additionally, a noise suppressor that operates in the frequency domain, like the spectral weighting filter, can leave artifacts in the output signal, such as musical noise, jet engine roar, running water, or the like.